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1000 results for “sanjay_ankur”

  1. FYI folks, the Open Source Brain cluster is being upgraded and migrated, so you may experience transient issues on the #OpenSourceBrain platforms. More information on the status page here:

    status.opensourcebrain.org/

    #OpenScience #Neuroscience #Neuroinformatics #NetPyNE #NWBExplorer

    CC: @sdurabernal

  2. FYI folks, the Open Source Brain cluster is being upgraded and migrated, so you may experience transient issues on the platforms. More information on the status page here:

    status.opensourcebrain.org/

    CC: @sdurabernal

  3. FYI folks, the Open Source Brain cluster is being upgraded and migrated, so you may experience transient issues on the #OpenSourceBrain platforms. More information on the status page here:

    status.opensourcebrain.org/

    #OpenScience #Neuroscience #Neuroinformatics #NetPyNE #NWBExplorer

    CC: @sdurabernal

  4. FYI folks, the Open Source Brain cluster is being upgraded and migrated, so you may experience transient issues on the #OpenSourceBrain platforms. More information on the status page here:

    status.opensourcebrain.org/

    #OpenScience #Neuroscience #Neuroinformatics #NetPyNE #NWBExplorer

    CC: @sdurabernal

  5. Upgraded to @fedora 44, see this awesome new "wellbeing" feature in 50!

    Upgrade to went smoothly as always. It hasn't been released yet, so you can wait for that to be sure.

  6. RT @INCForg on birdsite:

    Applications are open for
    's 2023.
    Thanks to sponsorship from
    , this event is free for participants!

    NeuroDataReHack 2023
    📅 Sep 5-8
    📍Granada, Spain

    Apply here by May 1: bit.ly/NWBsNDRH2023

  7. A new version of the Open Source Brain () model validation framework was just released. Please update your installations:

    ```
    pip install -U OSBModelValidation
    ```

    github.com/OpenSourceBrain/osb

    is a package that allows you to validate your models against different simulation engines---to ensure that you get the same behaviours on all these engines. Examples:

    github.com/OpenSourceBrain/.gi

  8. @gabrock94 I think either would do as long as it's well commented. The advantage with Jupyter notebooks is that one can use Binder/Google Collab etc. to run them without requiring a local setup.

    We're also developing a new version of where one can keep their data + code and use a full environment on our cloud instance:

    v2.opensourcebrain.org

    (Under heavy development, still Beta!)

  9. The Software WG software highlight is starting in ~20 minutes (1600UTC) !

    Michalis Pagkalos will discuss , a framework for incorporating dendrites to spiking neural networks

    ocns.github.io/SoftwareWG/2023

  10. Please join the Software WG at our next software highlight session on Feb 7 at 1600 UTC. Michalis Pagkalos will discuss , a framework for incorporating dendrites to spiking neural networks ocns.github.io/SoftwareWG/2023

  11. A lot of steps for starting new computational modelling projects in are repeatable and can be automated. So, I created a template to quickstart these projects. It includes boilerplate code and implements lots of other recommended/best practices in model and software development. Feedback/suggestions welcome!

    ankursinha.in/2025/09/23/a-coo

  12. #NeuroML supports all stages of the modelling life-cycle with a vast ecosystem of software tools: creating (#pyNeuroML, #neuroConstruct, #NEURON, #NetPyNE, #PyNN, #N2A), validating (pyNeuroML, #OMV, #SciUnit), visualising (pyNeuroML, #OSB, #NeuroML-DB), simulating (#NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN), model fitting/optimisation (#NeuroTune, #BluePyOpt, NetPyNE), sharing and reusing of models (OSB, NeuroML-DB, #NeuroMorpho.org). 7/x

  13. #NeuroML supports all stages of the modelling life-cycle with a vast ecosystem of software tools: creating (#pyNeuroML, #neuroConstruct, #NEURON, #NetPyNE, #PyNN, #N2A), validating (pyNeuroML, #OMV, #SciUnit), visualising (pyNeuroML, #OSB, #NeuroML-DB), simulating (#NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN), model fitting/optimisation (#NeuroTune, #BluePyOpt, NetPyNE), sharing and reusing of models (OSB, NeuroML-DB, #NeuroMorpho.org). 7/x

  14. #NeuroML supports all stages of the modelling life-cycle with a vast ecosystem of software tools: creating (#pyNeuroML, #neuroConstruct, #NEURON, #NetPyNE, #PyNN, #N2A), validating (pyNeuroML, #OMV, #SciUnit), visualising (pyNeuroML, #OSB, #NeuroML-DB), simulating (#NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN), model fitting/optimisation (#NeuroTune, #BluePyOpt, NetPyNE), sharing and reusing of models (OSB, NeuroML-DB, #NeuroMorpho.org). 7/x

  15. A number of software tools are available for construction and simulation of models: #NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN etc. These have their own features, styles, programming interfaces (APIs). This is great but it also means that researchers need to learn each of these individually to use them. It also means that tools and models developed for one don’t necessarily work for others and need to be manually converted. This is often a non-trivial task and limits model reuse. 3/x

  16. A number of software tools are available for construction and simulation of models: #NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN etc. These have their own features, styles, programming interfaces (APIs). This is great but it also means that researchers need to learn each of these individually to use them. It also means that tools and models developed for one don’t necessarily work for others and need to be manually converted. This is often a non-trivial task and limits model reuse. 3/x

  17. A number of software tools are available for construction and simulation of models: #NEURON, #NetPyNE, #Brian, #PyNN, #NEST, #MOOSE, #EDEN etc. These have their own features, styles, programming interfaces (APIs). This is great but it also means that researchers need to learn each of these individually to use them. It also means that tools and models developed for one don’t necessarily work for others and need to be manually converted. This is often a non-trivial task and limits model reuse. 3/x

  18. Please join the @INCF + @OCNS Software Working group on 9th July for our next meeting.

    Adam Tyson from the Sainsbury Wellcome Centre will talk about the software tools their group develops for systems neuroscience:

    ocns.github.io/SoftwareWG/2024

  19. PSA @fedora folks, to use ( and ) on your based browsers like and , pass `enable-experimental-web-platform-features` in the `qt.args` (for Qutebrowser, not sure what it is for Falkon):

    github.com/qutebrowser/qutebro